This invention relates generally to network-based information analytics and optimization processes, and more particularly to collaborative networking optimized with quality assessment of information provided by a network community.
Collaborative networking applications that are enabled through technologies such as Web 2.0 have brought forth the concept of crowd sourcing (also referred to as “the wisdom of crowds”) to several e-business and social networking sites. Web 2.0 refers to an increasingly popular type of web application that is primarily distinguished in its ability to enable network users to contribute information for collaboration and sharing. Common collaborative networking applications include, e.g., social software, web syndication, weblogs, and wilds, to name a few. The ability to tap into the wisdom of the crowds through these applications can be a great differentiating asset for an individual or organization that utilizes these applications. For example, content reviews provided by a large online community can be exploited to determine trends, forecasts, and similar data, thereby enabling a content service provider to implement various monetization strategies derived from this collective wisdom.
Some content companies have expressed the need to be able to leverage their social networks in ways that would involve their audience of consumers in aspects of the design and development of the products to be offered to these same consumers. In one aspect, these content companies highlighted the acute need to be able to properly synthesize the wisdom of “their” crowds, i.e., their consumers. The problem is that not every opinion received should be considered equal in terms of the expertise/reputation of those who contribute these opinions. Moreover, this problem may become acute with use-generated content given that exhaustive evaluation of such content can become burdensome for the hosting entity.
There is a need for an objective method for evaluating opinions or predictions gathered over a network from different entities and efficiently using these opinions or predictions to predict a future event (e.g., the success/failure of a product, movie, or a winner in elections, sports tournaments, etc).